Spark Programming in Python for Beginners with Apache Spark 3 - Spark Execution Modes and Cluster Managers

The video tutorial explains how Spark applications are executed on both local machines and clusters. It covers the roles of the driver and executors, and how Spark can run locally using a local cluster manager with multithreading. The tutorial also discusses running Spark with interactive tools like Spark shell and notebooks in client mode, where the driver runs locally but connects to a cluster. Finally, it explains cluster mode, where both the driver and executors run on the cluster, suitable for long-running jobs.

What are the implications of using a single local thread in Spark?

How does Spark handle executors when running in client mode?